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171. Head RD, Smythe ML, Oprea TI et al (1996) VALIDATE: A new method for the
receptor-based prediction of binding affinities of novel ligands. J Am Chem Soc 118:3959–
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incremental construction algorithm. J Mol Biol 261:470–489
173. Morris GM, Goodsell DS, Halliday RS et al (1998) Automated docking using a Lamarckian
genetic algorithm and an empirical binding free energy function. J Comput Chem 19:1639–
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174. Spyrakis F, Amadasi A, Fornabaio M et al (2007) The consequences of scoring docked
ligand conformations using free energy correlations. Eur J Med Chem 42:921–933. https://
doi.org/10.1016/j.ejmech.2006.12.037
175. Oprea TI, Marshall GR (1998) Receptor-based prediction of binding affinities. Perspect Drug
Discov Des 9:35–61
176. Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med
Chem 49:6789–6801. https://doi.org/10.1021/jm0608356
177. Empereur-Mot C, Guillemain H, Latouche A et al (2015) Predictiveness curves in virtual
screening. J Cheminform 7:52. https://doi.org/10.1186/s13321-015-0100-8
178. Bauer MR, Ibrahim TM, Vogel SM, Boeckler FM (2013) Evaluation and optimization of
virtual screening workflows with DEKOIS 2.0—a public library of challenging docking
benchmark sets. J Chem Inf Model 53:1447–1462
In Silico Structure-Based Prediction of Receptor–Ligand Binding …
169
482. https://doi.org/10.1021/ci500731a
157. Cornell WD, Cieplak P, Bayly CI et al (1995) A second generation force field for the
simulation of proteins, nucleic acids, and organic molecules. J Am Chem Soc 117:5179–
5197
158. MacKerell AD Jr, Bashford D, Bellott M et al (1998) All-atom empirical potential for
molecular modeling and dynamics studies of proteins. J Phys Chem B 102:3586–3616
159. Allen WJ, Balius TE, Mukherjee S et al (2015) DOCK 6: impact of new features and current
docking performance. J Comput Chem 36:1132–1156. https://doi.org/10.1002/jcc.23905
160. Simonson T, Archontis G, Karplus M (2002) Free energy simulations come of age:
protein-ligand recognition. Acc Chem Res 35:430–437
161. Kramer B, Rarey M, Lengauer T (1999) Evaluation of the FLEXX incremental construction
algorithm for protein–ligand docking. Proteins Struct Funct Bioinform 37:228–241
162. Böhm H-J (1994) The development of a simple empirical scoring function to estimate the
binding constant for a protein-ligand complex of known three-dimensional structure.
J Comput Aided Mol Des 8:243–256
163. Eldridge MD, Murray CW, Auton TR et al (1997) Empirical scoring functions: I. The
development of a fast empirical scoring function to estimate the binding affinity of ligands in
receptor complexes. J Comput Aided Mol Des 11:425–445
164. Böhm H-J (1992) LUDI: rule-based automatic design of new substituents for enzyme
inhibitor leads. J Comput Aided Mol Des 6:593–606
165. Friesner RA, Banks JL, Murphy RB et al (2004) Glide: a new approach for rapid, accurate
docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–
1749. https://doi.org/10.1021/jm0306430
166. Wang R, Lai L, Wang S (2002) Further development and validation of empirical scoring
functions for structure-based binding affinity prediction. J Comput Aided Mol Des 16:11–26
167. Sippl MJ (1995) Knowledge-based potentials for proteins. Curr Opin Struct Biol 5:229–235
168. Lyne PD (2002) Structure-based virtual screening: an overview. Drug Discov Today
7:1047–1055. https://doi.org/10.1016/s1359-6446(02)02483-2
169. Muegge I (2000) A knowledge-based scoring function for protein-ligand interactions:
probing the reference state. Perspect Drug Discov Des 20:99–114
170. Gohlke H, Hendlich M, Klebe G (2000) Knowledge-based scoring function to predict
protein-ligand interactions. J Mol Biol 295:337–356
171. Head RD, Smythe ML, Oprea TI et al (1996) VALIDATE: A new method for the
receptor-based prediction of binding affinities of novel ligands. J Am Chem Soc 118:3959–
3969
172. Rarey M, Kramer B, Lengauer T, Klebe G (1996) A fast flexible docking method using an
incremental construction algorithm. J Mol Biol 261:470–489
173. Morris GM, Goodsell DS, Halliday RS et al (1998) Automated docking using a Lamarckian
genetic algorithm and an empirical binding free energy function. J Comput Chem 19:1639–
1662
174. Spyrakis F, Amadasi A, Fornabaio M et al (2007) The consequences of scoring docked
ligand conformations using free energy correlations. Eur J Med Chem 42:921–933. https://
doi.org/10.1016/j.ejmech.2006.12.037
175. Oprea TI, Marshall GR (1998) Receptor-based prediction of binding affinities. Perspect Drug
Discov Des 9:35–61
176. Huang N, Shoichet BK, Irwin JJ (2006) Benchmarking sets for molecular docking. J Med
Chem 49:6789–6801. https://doi.org/10.1021/jm0608356
177. Empereur-Mot C, Guillemain H, Latouche A et al (2015) Predictiveness curves in virtual
screening. J Cheminform 7:52. https://doi.org/10.1186/s13321-015-0100-8
178. Bauer MR, Ibrahim TM, Vogel SM, Boeckler FM (2013) Evaluation and optimization of
virtual screening workflows with DEKOIS 2.0—a public library of challenging docking
benchmark sets. J Chem Inf Model 53:1447–1462
In Silico Structure-Based Prediction of Receptor–Ligand Binding …
169